Biomedical Engineering Reference

In-Depth Information

combine hold with freely for measurement as the head motion in freely is too large

for a static positioning scenario (cf.
Sect. 2.3.1
).

2.2.4 Error Calculation

We cannot assume that the sensor to coil distance or the sensor position are exactly

the same for each single measurement. As this may change the absolute induced

electric field magnitude, we cannot apply an absolute error measure. Instead, we

calculate the decrease in the magnitude of the induced electric field as a relative

error measure. At each timestamp t we compute the error relative to the initial

field. The change in magnitude is defined as:

2

E
ð
0
Þ

err
rel
ð
t
Þ¼
1

;

E
ð
t
Þ

2

err
rel
ð
t
Þ2½
0
;
1
;

ð
2
:
1
Þ

where
kk
2
represents the Euclidean norm.

Our field sensor additionally measures the in-plane orientation of the electric

field (see
Sect. 3.1
for the importance of coil orientation and direction of the

induced electric field). We obtain the change in the angle as

r
ð
t
Þ¼
arctan
E
y
ð
0
Þ

E
x
ð
0
Þ
arctan
E
y
ð
t
Þ

ð
2
:
2
Þ

E
x
ð
t
Þ

based on the x and y component of the electric field E.

2.2.5 Statistical Analysis

Statistical analysis is carried out with IBM SPSS Statistics version 20 (IBM

Deutschland GmbH, Ehningen, Germany).

As we are interested in the effect of robotized TMS compared to standard TMS

scenarios, we perform an analysis of variance (ANOVA) comparing the means of

hold-and-restrain, hold-and-rest and robot-freely for statistical analysis. Note that a

two-factorial ANOVA cannot be used as we cannot measure free with a coil holder.

2.3 Impact of Head Motion on TMS

2.3.1 Head Motion

Figure
2.7
visualizes the head motion of the three basic scenarios over time for all

subjects. In the two subplots the mean amplitude of translational and rotational

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